This week we begin with an article by Harvard Business Review on how the pandemic has called for new methods in predicting consumer demand, using forecast models based on new data sets. Next, we have enclosed a map by the New York Times which geographically shows how many people headed to the advice of public health officials and stayed at home for Thanksgiving. The following story is on how scientists in Virginia are using mathematical modeling to predict floods by engaging hundreds of volunteers in the mapping of high-level tides. Then we have an article on universities leveraging Facebook to track trends related to COVID-19 infections using voluntary surveys. To end, we have enclosed a video in which experts talk about the ethical issues of Artificial Intelligence and how AI is transforming the world as we know it.
Predicting Consumer Demand In An Unpredictable World
Covid-19 has shattered the demand forecasts that guide retailers and suppliers of consumer goods and services in figuring out how much to order or manufacture, where to stock inventory, and how much to advertise or discount. Early on during the pandemic, sudden lockdowns and a shift to working from home caused panic buying of many food items and household goods.
A Detailed Map of Where Americans Are Staying Home for Thanksgiving
Public health officials have been pleading with Americans to stay home this year for Thanksgiving. And, despite busy airports this past weekend, most people plan to follow their advice, according to a huge survey asking Americans about their holiday plans. The map shows the geographic variation in those plans, and there are partisan splits, too. But even among Republicans, two-thirds are forgoing a large traditional Thanksgiving.
Where Will The Next Big Flood Hit?
Christina Laughlin usually does whatever she can to avoid the flooding that plagues her neighborhood in Norfolk, Virginia, on the Chesapeake Bay. But on a blustery Sunday morning in October 2019, she donned a windbreaker and rain boots, grabbed her battered smartphone, and deliberately headed straight to the high-water line.
This Database Is Finally Holding AI Accountable
The Artificial Intelligence Incident Database (AIID) is a crowdsourced platform with intentions to wrangle in the Wild West of AI. “Fool me once, shame on me; fool me twice shame on you,” comes to mind, as the platform is being used to document and compile AI failures so they won’t happen again.
Universities Tracking COVID-19 Trends Through Facebook Surveys
As health officials around the world tack COVID-19 infection rates, two universities in the U.S. have partnered with Facebook to try to predict infections with real-time survey data. Dr. Alex Reinhart, an assistant teaching professor of statistics and data science at Carnegie Mellon University and a member of the Delphi Group, says that as health officials were struggling with testing capacity in the spring, they realized they might be able to predict infections by analyzing social media.
Do You Know AI or AI knows You Better? Thinking Ethics of AI
As health officials around the world tack COVID-19 infection rates, two universities in the U.S. have partnered with Facebook to try to predict infections with real-time survey data. Dr. Alex Reinhart, an assistant teaching professor of statistics and data science at Carnegie Mellon University and a member of the Delphi Group, says that as health officials were struggling with testing capacity in the spring, they realized they might be able to predict infections by analyzing social media.
Source: https://mailchi.mp/zigram/data-asset-weekly-dispatch_02_december_2
